code: def test_beam_parse(examples, beam_width):
      nlp = Language()
      parser = nlp.add_pipe("beam_parser")
      parser.cfg["beam_width"] = beam_width
      parser.add_label("nsubj")
      parser.initialize(lambda: examples)
      doc = nlp.make_doc("Australia is a country")
      parser(doc)
  
imports: import hypothesis
  import hypothesis.strategies
  import numpy
  import pytest
  from thinc.tests.strategies import ndarrays_of_shape
  from spacy.language import Language
  from spacy.pipeline._parser_internals._beam_utils import BeamBatch
  from spacy.pipeline._parser_internals.arc_eager import ArcEager
  from spacy.pipeline._parser_internals.stateclass import StateClass
  from spacy.tokens import Doc
  from spacy.training import Example
  from spacy.vocab import Vocab
label_desc: Use image node_id 16 for calling a global function with example usage: test_beam_parse(examples, beam_width) without return types